ChatGPT is a chatbot launched by OpenAI in November 2022. It is built on top of OpenAI’s GPT-3 family of large language models, and is fine-tuned with both supervised and reinforcement learning techniques.
ChatGPT was launched as a prototype on November 30, 2022, and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. Following the release of ChatGPT, OpenAI reportedly doubled in value to $29 billion.
There has been a huge amount of interest with more than a million people signing up to try the platform in the first five days. Global tech media was buzzing, with the internationally available BBC Click tech magazine show doing a feature. This was followed by the TopGear car enthusiasts program actually posting a chat with the bot on its website.
The reason for this is that ChatGPT interacts with users conversationally, making it possible for the chatbot to answer follow-up questions, challenge incorrect arguments, admit its mistakes, and more.
Whether you need the foundation of a speech for a seminar, or a complex topic explained simply so you can write a blog post for your recruitment website, ChatGPT has attracted a lot of fans. But what are the implications for the recruitment sector and staffing agencies?
Typical chatbots are configured using logic flows to provide automated responses to enquiries sent through email, chat messengers and social channels like WhatsApp. Typically, in recruitment, these chatbots might look for keywords like ‘vacancy’ or ‘hourly rate’ and then provide appropriate responses.
When it comes to knowledge and the written word, ChatGPT takes automation to a new level, the level of ‘true’ AI. For recruitment and staffing agencies, the software could write a barebones job description for a job board post or an entire blog about a complex topic like taxation for freelance and contract workers for any region of the world.
However, OPenAI warns ChatGPT can produce problematic answers. For the recruitment sector, this means such AI tools may have unintended consequences, such as reinforcing existing biases in the recruitment process. Some examples of this include:
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